Traditional semiconductor based digital electronic processors are typically serial devices processing data in a serial manner, i.e. a first operation is performed on a first set of data before a second set of data is fetched and operated upon. Although advents in semiconductor based vocoders and processor architectures, such as predictive branching and higher microprocessor speed, have provided systems capable of performing increasingly faster operations, the fundamental serial structure of semiconductor processing systems inherent in the device technology (e.g., von Neumann architecture) have limited the speed at which complex processing algorithms such as video signal processing and compression may be performed with a general purpose semiconductor based processor. Further, although specialized semiconductor processors have been developed having architectures optimized for signal processing algorithms (e.g., digital signal processors, Harvard architecture), semiconductor devices still exhibit a signal processing limit. These problems become apparent when it is desired to transmit video or audio over a limited bandwidth channel. Since video and audio signals many times have a greater bandwidth than the channel over which it is desired to transmit, compression algorithms are utilized to reduce the bandwidth such that transmission over the lower bandwidth channel may be achieved. However, video and some audio compression algorithms require large amounts of processing power. Using traditional semiconductor processors to perform the compression algorithms in real-time or near real-time many times requires too much processing time to accomplish high quality image or audio compression. Therefore, at best, semiconductor processors only provide lossy video compression (where some information quality and content is sacrificed) as real time compression is approached.
However, optical processors using holographic image processing/classification techniques are capable of processing information in parallel such that much more complex image processing algorithms such as compression, correlations, and transform decompositions may be processed in much shorter amount of time than with traditional semiconductor processors. Such optically implemented image classification and processing algorithms may provide optimized transmission of video, image and graphics file signals over lower bandwidth channels. Furthermore, by combining an optical processor with a media communication system, voice command recognition, control and neural network signal processing may be implemented with the system by taking advantage of the parallel processing and data classification provided by an optical processing system. Thus, there lies a need for a media processing and transmission system that utilizes optical processing to provide faster and more optimized transmission of video and audio signals over lower bandwidth communications channels and that further utilizes optical processing to implement voice command recognition and neural network decision processing.